The Sweden Cancerome Analysis Network - Breast (SCAN-B) Initiative: a large-scale multicenter infrastructure towards implementation of breast cancer genomic analyses in the clinical routine

High Caveolin-1 mRNA expression in triple-negative breast cancer is associated with an aggressive tumor microenvironment, chemoresistance, and poor clinical outcome

BACKGROUND

Currently, there are few treatment-predictive and prognostic biomarkers in triple-negative breast cancer (TNBC). Caveolin-1 (CAV1) is linked to chemoresistance and several important processes involved in tumor progression and metastasis, such as epithelial-mesenchymal transition (EMT). Herein, we report that high CAV1 gene expression is an independent factor of poor prognosis in TNBC.

METHODS

CAV1 gene expression was compared across different molecular features (e.g., PAM50 subtypes). CAV1 expression was assessed in relation to clinical outcomes using Cox regression adjusted for clinicopathological predictors. Differential gene expression and gene set enrichment analyses were applied to compare high- and low-expressing CAV1 tumors. Tumor microenvironment composition of high- and low-expressing CAV1 tumors was estimated using ECOTYPER. Tumor tissue microarrays were used to evaluate CAV1 protein levels in stromal and malignant cells.

RESULTS

In the SCAN-B (n = 525) and GSE31519 (n = 327) cohorts, patients with CAV1-high tumors had an increased incidence of early recurrence adjusted HR 1.78 (95% CI 1.12-2.81) and 2.20 (95% CI 1.39-3.47), respectively. In further analysis, high CAV1 gene expression was associated with a molecular profile indicating altered metabolism, neovascularization, chemoresistance, EMT, suppressed immune response, and active tumor microenvironment. Protein levels of CAV1 in malignant and stromal cells were not correlated with CAV1 gene expression.

CONCLUSION

CAV1 gene expression in TNBC is a biomarker that merits further investigation in clinical trials and as a therapeutic target.

The VEGF-Hypoxia Signature Is Upregulated in Basal-like Breast Tumors from Women of African Ancestry and Associated with Poor Outcomes in Breast Cancer

PURPOSE

Black women experience the highest breast cancer mortality rate compared with women of other racial/ethnic groups. To gain a deeper understanding of breast cancer heterogeneity across diverse populations, we examined a VEGF-hypoxia gene expression signature in breast tumors from women of diverse ancestry.

EXPERIMENTAL DESIGN

We developed a NanoString nCounter gene expression panel and applied it to breast tumors from Nigeria (n = 182) and the University of Chicago (Chicago, IL; n = 161). We also analyzed RNA sequencing data from Nigeria (n = 84) and The Cancer Genome Atlas (TCGA) datasets (n = 863). Patient prognosis was analyzed using multiple datasets.

RESULTS

The VEGF-hypoxia signature was highest in the basal-like subtype compared with other subtypes, with greater expression in Black women compared with White women. In TCGA dataset, necrotic breast tumors had higher scores for the VEGF-hypoxia signature compared with non-necrosis tumors (P < 0.001), with the highest proportion in the basal-like subtype. Furthermore, necrotic breast tumors have higher scores for the proliferation signature, suggesting an interaction between the VEGF-hypoxia signature, proliferation, and necrosis. T-cell gene expression signatures also correlated with the VEGF-hypoxia signature when testing all tumors in TCGA dataset. Finally, we found a significant association of the VEGF-hypoxia profile with poor outcomes when using all patients in the METABRIC (P < 0.0001) and SCAN-B datasets (P = 0.002).

CONCLUSIONS

These data provide further evidence for breast cancer heterogeneity across diverse populations and molecular subtypes. Interventions selectively targeting VEGF-hypoxia and the immune microenvironment have the potential to improve overall survival in aggressive breast cancers that disproportionately impact Black women in the African Diaspora.

Kataegis in clinical and molecular subgroups of primary breast cancer

Kataegis is a hypermutation phenomenon characterized by localized clusters of single base pair substitution (SBS) reported in multiple cancer types. Despite a high frequency in breast cancer, large-scale analyses of kataegis patterns and associations with clinicopathological and molecular variables in established breast cancer subgroups are lacking. Therefore, WGS profiled primary breast cancers (n = 791) with associated clinical and molecular data layers, like RNA-sequencing data, were analyzed for kataegis frequency, recurrence, and associations with genomic contexts and functional elements, transcriptional patterns, driver alterations, homologous recombination deficiency (HRD), and prognosis in tumor subgroups defined by ER, PR, and HER2/ERBB2 status. Kataegis frequency was highest in the HER2-positive(p) subgroups, including both ER-negative(n)/positive(p) tumors (ERnHER2p/ERpHER2p). In TNBC, kataegis was neither associated with PAM50 nor TNBC mRNA subtypes nor with distant relapse in chemotherapy-treated patients. In ERpHER2n tumors, kataegis was associated with aggressive characteristics, including PR-negativity, molecular Luminal B subtype, higher mutational burden, higher grade, and expression of proliferation-associated genes. Recurrent kataegis loci frequently targeted regions commonly amplified in ER-positive tumors, while few recurrent loci were observed in TNBC. SBSs in kataegis loci appeared enriched in regions of open chromatin. Kataegis status was not associated with HRD in any subgroup or with distinct transcriptional patterns in unsupervised or supervised analysis. In summary, kataegis is a common hypermutation phenomenon in established breast cancer subgroups, particularly in HER2p subgroups, coinciding with an aggressive tumor phenotype in ERpHER2n disease. In TNBC, the molecular implications and associations of kataegis are less clear, including its prognostic value.

Caveolin-1 gene expression provides additional prognostic information combined with PAM50 risk of recurrence (ROR) score in breast cancer

Combining information from the tumor microenvironment (TME) with PAM50 Risk of Recurrence (ROR) score could improve breast cancer prognostication. Caveolin-1 (CAV1) is a marker of an active TME. CAV1 is a membrane protein involved in cell signaling, extracellular matrix organization, and tumor-stroma interactions. We sought to investigate CAV1 gene expression in relation to PAM50 subtypes, ROR score, and their joint prognostic impact. CAV1 expression was compared between PAM50 subtypes and ROR categories in two cohorts (SCAN-B, n = 5326 and METABRIC, n = 1980). CAV1 expression was assessed in relation to clinical outcomes using Cox regression and adjusted for clinicopathological predictors. Effect modifications between CAV1 expression and ROR categories on clinical outcome were investigated using multiplicative and additive two-way interaction analyses. Differential gene expression and gene set enrichment analyses were applied to compare high and low expressing CAV1 tumors. All samples expressed CAV1 with the highest expression in the Normal-like subtype. Gene modules consistent with epithelial-mesenchymal transition (EMT), hypoxia, and stromal activation were associated with high CAV1 expression. CAV1 expression was inversely associated with ROR category. Interactions between CAV1 expression and ROR categories were observed in both cohorts. High expressing CAV1 tumors conferred worse prognosis only within the group classified as ROR high. ROR gave markedly different prognostic information depending on the underlying CAV1 expression. CAV1, a potential mediator between the malignant cells and TME, could be a useful biomarker that enhances and further refines PAM50 ROR risk stratification in patients with ROR high tumors and a potential therapeutic target.

Prognostic value of HER2DX in early-stage HER2-positive breast cancer: a comprehensive analysis of 757 patients in the Sweden Cancerome Analysis Network-Breast dataset (SCAN-B)

BACKGROUND

The HER2DX risk-score has undergone rigorous validation in prior investigations involving patients with early-stage human epidermal growth factor receptor 2 (HER2)-positive (HER2+) breast cancer. In this study, we present the outcomes of the HER2DX risk-score within the most recent release of the Sweden Cancerome Analysis Network-Breast (SCAN-B) HER2+ cohort. This updated examination benefits from a larger patient sample, an extended follow-up duration, and detailed treatment information.

MATERIALS AND METHODS

Clinical and RNAseq data from the SCAN-B dataset were retrieved from Gene Expression Omnibus (GSE81538). Among the 6600 patients, 819 had HER2+ breast cancer, with 757 individuals with research-based HER2DX risk-scores and corresponding survival outcomes. The HER2DX risk-score was evaluated (i) as a continuous variable and (ii) using predefined cut-offs. The primary endpoint for this study was overall survival (OS). The Kaplan-Meier method and Cox models were used to estimate OS and a multistate model with four states was fitted to better characterize patients' follow-up.

RESULTS

The median follow-up time was 7.5 years (n = 757). The most common systemic therapy was chemotherapy with trastuzumab (82.0%) and most tumors were classified as T1-T2 (97.1%). The HER2DX risk-score as a continuous variable was significantly associated with OS after adjustment for clinical variables and treatment regimen [hazard ratios (HR) per 10-unit increment = 1.31, 95% confidence interval (CI) 1.13-1.51, P < 0.001] as well as within predefined risk groups (high versus low; HR = 2.57, 95% CI 1.36-4.85, P < 0.001). Patients classified as HER2DX high-risk also had higher risk of (i) breast cancer recurrence and (ii) death without previous recurrence. Within the subgroup of HER2+ T1N0 tumors (n = 297), those classified as high-risk demonstrated inferior OS compared to low-risk tumors (7-year OS 77.8% versus 96.8%, P < 0.001). The HER2DX mRNA ERBB2 score was associated with clinical HER2 status (area under the receiver operating characteristic curve = 0.91).

CONCLUSIONS

In patients with early-stage HER2+ breast cancer, HER2DX risk-score provides prognostic information beyond clinicopathological variables, including treatment regimen with or without trastuzumab.

Digital PCR quantification of ultrahigh ERBB2 copy number identifies poor breast cancer survival after trastuzumab

HER2/ERBB2 evaluation is necessary for treatment decision-making in breast cancer (BC), however current methods have limitations and considerable variability exists. DNA copy number (CN) evaluation by droplet digital PCR (ddPCR) has complementary advantages for HER2/ERBB2 diagnostics. In this study, we developed a single-reaction multiplex ddPCR assay for determination of ERBB2 CN in reference to two control regions, CEP17 and a copy-number-stable region of chr. 2p13.1, validated CN estimations to clinical in situ hybridization (ISH) HER2 status, and investigated the association of ERBB2 CN with clinical outcomes. 909 primary BC tissues were evaluated and the area under the curve for concordance to HER2 status was 0.93 and 0.96 for ERBB2 CN using either CEP17 or 2p13.1 as reference, respectively. The accuracy of ddPCR ERBB2 CN was 93.7% and 94.1% in the training and validation groups, respectively. Positive and negative predictive value for the classic HER2 amplification and non-amplification groups was 97.2% and 94.8%, respectively. An identified biological "ultrahigh" ERBB2 ddPCR CN group had significantly worse survival within patients treated with adjuvant trastuzumab for both recurrence-free survival (hazard ratio, HR: 3.3; 95% CI 1.1-9.6; p = 0.031, multivariable Cox regression) and overall survival (HR: 3.6; 95% CI 1.1-12.6; p = 0.041). For validation using RNA-seq data as a surrogate, in a population-based SCAN-B cohort (NCT02306096) of 682 consecutive patients receiving adjuvant trastuzumab, the ultrahigh-ERBB2 mRNA group had significantly worse survival. Multiplex ddPCR is useful for ERBB2 CN estimation and ultrahigh ERBB2 may be a predictive factor for decreased long-term survival after trastuzumab treatment.

Investigating the immunological function of alpha-2-glycoprotein 1, zinc-binding in regulating tumor response in the breast cancer microenvironment

BACKGROUND

Alpha-2-glycoprotein 1, zinc-binding (ZAG), a secreted protein encoded by the AZGP1 gene, is structurally similar to HLA class I. Despite its presumed immunological function, little is known about its role in tumor immunity. In this study, we thus aimed to determine the relationship between the expression of AZGP1/ZAG and the immunological profiles of breast cancer tissues at both the gene and protein level.

METHODS

Using a publicly available gene expression dataset from a large-scale breast cancer cohort, we conducted gene set enrichment analysis (GSEA) to screen the biological processes associated with AZGP1. We analyzed the correlation between AZGP1 expression and immune cell composition in breast cancer tissues, estimated using CIBERSORTx. Previously, we evaluated the infiltration of 11 types of immune cells for 45 breast cancer tissues using flow cytometry (FCM). ZAG expression was evaluated by immunohistochemistry on these specimens and analyzed for its relationship with immune cell infiltration. The action of ZAG in M1/M2 polarization models using primary cultures of human peripheral blood mononuclear cells (PBMC)-derived macrophage (Mφ) was analyzed based on the expression of M1/M2 markers (CD86, CD80/CD163, MRC1) and HLA class I/II by FCM.

RESULTS

AZGP1 expression was negatively correlated with multiple immunological processes and specific immune cell infiltration including Mφ M1 using GSEA and CIBERSORTx. ZAG expression was associated with decreased infiltration of monocytes/macrophages, non-classical monocytes, and myeloid-derived suppressor cells in tumor tissues assessed using FCM. In in vitro analyses, ZAG decreased the expression of CD80, CD163, MRC1, and HLA classes I/II in the M1 polarization model and the expression of CD163 and MRC1 in the M2 polarization model.

CONCLUSION

ZAG is suggested to be a novel immunoregulatory factor affecting the Mφ phenotype in breast cancer tissues.

DriverDBv4: a multi-omics integration database for cancer driver gene research

Advancements in high-throughput technology offer researchers an extensive range of multi-omics data that provide deep insights into the complex landscape of cancer biology. However, traditional statistical models and databases are inadequate to interpret these high-dimensional data within a multi-omics framework. To address this limitation, we introduce DriverDBv4, an updated iteration of the DriverDB cancer driver gene database (http://driverdb.bioinfomics.org/). This updated version offers several significant enhancements: (i) an increase in the number of cohorts from 33 to 70, encompassing approximately 24 000 samples; (ii) inclusion of proteomics data, augmenting the existing types of omics data and thus expanding the analytical scope; (iii) implementation of multiple multi-omics algorithms for identification of cancer drivers; (iv) new visualization features designed to succinctly summarize high-context data and redesigned existing sections to accommodate the increased volume of datasets and (v) two new functions in Customized Analysis, specifically designed for multi-omics driver identification and subgroup expression analysis. DriverDBv4 facilitates comprehensive interpretation of multi-omics data across diverse cancer types, thereby enriching the understanding of cancer heterogeneity and aiding in the development of personalized clinical approaches. The database is designed to foster a more nuanced understanding of the multi-faceted nature of cancer.

Gene-Expression Profiling to Decipher Breast Cancer Inter- and Intratumor Heterogeneity

Breast cancer is heterogeneous and differs substantially across different tumors (intertumor heterogeneity) and even within an individual tumor (intratumor heterogeneity). Gene-expression profiling has considerably impacted our understanding of breast cancer biology. Four main "intrinsic subtypes" of breast cancer (i.e., luminal A, luminal B, HER2-enriched, and basal-like) have been consistently identified by gene expression, showing significant prognostic and predictive value in multiple clinical scenarios. Thanks to the molecular profiling of breast tumors, breast cancer is a paradigm of treatment personalization. Several standardized prognostic gene-expression assays are presently being used in the clinic to guide treatment decisions. Moreover, the development of single-cell-level resolution molecular profiling has allowed us to appreciate that breast cancer is also heterogeneous within a single tumor. There is an evident functional heterogeneity within the neoplastic and tumor microenvironment cells. Finally, emerging insights from these studies suggest a substantial cellular organization of neoplastic and tumor microenvironment cells, thus defining breast cancer ecosystems and highlighting the importance of spatial localizations.

MRE11 liberates cGAS from nucleosome sequestration during tumorigenesis

Oncogene-induced replication stress generates endogenous DNA damage that activates cGAS-STING-mediated signalling and tumour suppression1-3. However, the precise mechanism of cGAS activation by endogenous DNA damage remains enigmatic, particularly given that high-affinity histone acidic patch (AP) binding constitutively inhibits cGAS by sterically hindering its activation by double-stranded DNA (dsDNA)4-10. Here we report that the DNA double-strand break sensor MRE11 suppresses mammary tumorigenesis through a pivotal role in regulating cGAS activation. We demonstrate that binding of the MRE11-RAD50-NBN complex to nucleosome fragments is necessary to displace cGAS from acidic-patch-mediated sequestration, which enables its mobilization and activation by dsDNA. MRE11 is therefore essential for cGAS activation in response to oncogenic stress, cytosolic dsDNA and ionizing radiation. Furthermore, MRE11-dependent cGAS activation promotes ZBP1-RIPK3-MLKL-mediated necroptosis, which is essential to suppress oncogenic proliferation and breast tumorigenesis. Notably, downregulation of ZBP1 in human triple-negative breast cancer is associated with increased genome instability, immune suppression and poor patient prognosis. These findings establish MRE11 as a crucial mediator that links DNA damage and cGAS activation, resulting in tumour suppression through ZBP1-dependent necroptosis.

Improved detection of clinically relevant fusion transcripts in cancer by machine learning classification

BACKGROUND

Genomic rearrangements in cancer cells can create fusion genes that encode chimeric proteins or alter the expression of coding and non-coding RNAs. In some cancer types, fusions involving specific kinases are used as targets for therapy. Fusion genes can be detected by whole genome sequencing (WGS) and targeted fusion panels, but RNA sequencing (RNA-Seq) has the advantageous capability of broadly detecting expressed fusion transcripts.

RESULTS

We developed a pipeline for validation of fusion transcripts identified in RNA-Seq data using matched WGS data from The Cancer Genome Atlas (TCGA) and applied it to 910 tumors from 11 different cancer types. This resulted in 4237 validated gene fusions, 3049 of them with at least one identified genomic breakpoint. Utilizing validated fusions as true positive events, we trained a machine learning classifier to predict true and false positive fusion transcripts from RNA-Seq data. The final precision and recall metrics of the classifier were 0.74 and 0.71, respectively, in an independent dataset of 249 breast tumors. Application of this classifier to all samples with RNA-Seq data from these cancer types vastly extended the number of likely true positive fusion transcripts and identified many potentially targetable kinase fusions. Further analysis of the validated gene fusions suggested that many are created by intrachromosomal amplification events with microhomology-mediated non-homologous end-joining.

CONCLUSIONS

A classifier trained on validated fusion events increased the accuracy of fusion transcript identification in samples without WGS data. This allowed the analysis to be extended to all samples with RNA-Seq data, facilitating studies of tumor biology and increasing the number of detected kinase fusions. Machine learning could thus be used in identification of clinically relevant fusion events for targeted therapy. The large dataset of validated gene fusions generated here presents a useful resource for development and evaluation of fusion transcript detection algorithms.

PAIRWISE NONLINEAR DEPENDENCE ANALYSIS OF GENOMIC DATA

In The Cancer Genome Atlas (TCGA) data set, there are many interesting nonlinear dependencies between pairs of genes that reveal important relationships and subtypes of cancer. Such genomic data analysis requires a rapid, powerful and interpretable detection process, especially in a high-dimensional environment. We study the nonlinear patterns among the expression of pairs of genes from TCGA using a powerful tool called Binary Expansion Testing. We find many nonlinear patterns, some of which are driven by known cancer subtypes, some of which are novel.

Tamoxifen Response at Single-Cell Resolution in Estrogen Receptor-Positive Primary Human Breast Tumors

PURPOSE

In estrogen receptor-positive (ER+)/HER2- breast cancer, multiple measures of intratumor heterogeneity are associated with a worse response to endocrine therapy. We sought to develop a novel experimental model to measure heterogeneity in response to tamoxifen treatment in primary breast tumors.

EXPERIMENTAL DESIGN

To investigate heterogeneity in response to treatment, we developed an operating room-to-laboratory pipeline for the collection of live normal breast specimens and human tumors immediately after surgical resection for processing into single-cell workflows for experimentation and genomic analyses. Live primary cell suspensions were treated ex vivo with tamoxifen (10 μmol/L) or control media for 12 hours, and single-cell RNA libraries were generated using the 10X Genomics droplet-based kit.

RESULTS

In total, we obtained and processed normal breast tissue from two women undergoing reduction mammoplasty and tumor tissue from 10 women with ER+/HER2- invasive breast carcinoma. We demonstrate differences in tamoxifen response by cell type and identify distinctly responsive and resistant subpopulations within the malignant cell compartment of human tumors. Tamoxifen resistance signatures from resistant subpopulations predict poor outcomes in two large cohorts of ER+ breast cancer patients and are enriched in endocrine therapy-resistant tumors.

CONCLUSIONS

This novel ex vivo model system now provides the foundation to define responsive and resistant subpopulations within heterogeneous human tumors, which can be used to develop precise single cell-based predictors of response to therapy and to identify genes and pathways driving therapeutic resistance.

Chromatin insulation orchestrates matrix metalloproteinase gene cluster expression reprogramming in aggressive breast cancer tumors

BACKGROUND

Triple-negative breast cancer (TNBC) is an aggressive subtype that exhibits a high incidence of distant metastases and lacks targeted therapeutic options. Here we explored how the epigenome contributes to matrix metalloprotease (MMP) dysregulation impacting tumor invasion, which is the first step of the metastatic process.

METHODS

We combined RNA expression and chromatin interaction data to identify insulator elements potentially associated with MMP gene expression and invasion. We employed CRISPR/Cas9 to disrupt the CCCTC-Binding Factor (CTCF) binding site on an insulator element downstream of the MMP8 gene (IE8) in two TNBC cellular models. We characterized these models by combining Hi-C, ATAC-seq, and RNA-seq with functional experiments to determine invasive ability. The potential of our findings to predict the progression of ductal carcinoma in situ (DCIS), was tested in data from clinical specimens.

RESULTS

We explored the clinical relevance of an insulator element located within the Chr11q22.2 locus, downstream of the MMP8 gene (IE8). This regulatory element resulted in a topologically associating domain (TAD) boundary that isolated nine MMP genes into two anti-correlated expression clusters. This expression pattern was associated with worse relapse-free (HR = 1.57 [1.06 - 2.33]; p = 0.023) and overall (HR = 2.65 [1.31 - 5.37], p = 0.005) survival of TNBC patients. After CRISPR/Cas9-mediated disruption of IE8, cancer cells showed a switch in the MMP expression signature, specifically downregulating the pro-invasive MMP1 gene and upregulating the antitumorigenic MMP8 gene, resulting in reduced invasive ability and collagen degradation. We observed that the MMP expression pattern predicts DCIS that eventually progresses into invasive ductal carcinomas (AUC = 0.77, p < 0.01).

CONCLUSION

Our study demonstrates how the activation of an IE near the MMP8 gene determines the regional transcriptional regulation of MMP genes with opposing functional activity, ultimately influencing the invasive properties of aggressive forms of breast cancer.

Discovery and identification of the prognostic significance and potential mechanism of FMO2 in breast cancer

BACKGROUND

Flavin containing dimethylaniline monoxygenase 2 (FMO2), is downexpressed in diverse tumors and displays vital roles in tumorigenesis. However, the prognostic value and potential mechanism of FMO2 in breast cancer remain unclear.

METHODS

The expression of FMO2 was analyzed and the relationship between FMO2 expression level and clinical indicators in breast cancer was analyzed. Then the prognostic value of FMO2 in breast cancer was assessed. The FMO2-correlated genes were obtained, and the highest-ranked gene was chosen. The expression, therapeutic responder analysis, and gene set enrichment analysis of the highest-ranked gene were conducted.

RESULTS

FMO2 was downregulated in breast cancer and was closely related to clinical indicators. Patients with decreased FMO2 expression showed poor overall survival, post-progression survival, relapse-free survival, and distant metastasis-free survival. FMO2 correlates with N/ER/PR subgroups in breast cancer and patients with high FMO2 levels were sensitive to anti-programmed cell death protein 1, anti-programmed death-ligand 1, and anti-cytotoxic T-lymphocyte antigen 4 immunotherapies. Mechanically, FMO2 was positively and highly correlated with secreted Frizzled-related protein 1 (SFRP1), which was downregulated in breast cancer due to hypermethylation. Moreover, SFRP1 was correlated to pathological complete response and relapse-free survival status at 5 years regardless of any chemotherapy, hormone therapy, and anti-HER2 therapy. Gene set enrichment analysis revealed enrichment of component and coagulation cascades, focal adhesion, protein export, and spliceosome.

CONCLUSIONS

FMO2 was lower expressed in breast cancer than normal tissues and contributes to subtype classification and prognosis prediction with co-expressed SFRP1.

MicroRNAs as Molecular Biomarkers for the Characterization of Basal-like Breast Tumor Subtype

Breast cancer is a heterogeneous disease highlighted by the presence of multiple tumor variants and the basal-like breast cancer (BLBC) is considered to be the most aggressive variant with limited therapeutics and a poor prognosis. Though the absence of detectable protein and hormonal receptors as biomarkers hinders early detection, the integration of genomic and transcriptomic profiling led to the identification of additional variants in BLBC. The high-throughput analysis of tissue-specific micro-ribonucleic acids (microRNAs/miRNAs) that are deemed to have a significant role in the development of breast cancer also displayed distinct expression profiles in each subtype of breast cancer and thus emerged to be a robust approach for the precise characterization of the BLBC subtypes. The classification schematic of breast cancer is still a fluid entity that continues to evolve alongside technological advancement, and the transcriptomic profiling of tissue-specific microRNAs is projected to aid in the substratification and diagnosis of the BLBC tumor subtype. In this review, we summarize the current knowledge on breast tumor classification, aim to collect comprehensive evidence based on the microRNA expression profiles, and explore their potential as prospective biomarkers of BLBC.

Malmö Breast ImaginG database: objectives and development

Purpose

We describe the design and implementation of the Malmö Breast ImaginG (M-BIG) database, which will support research projects investigating various aspects of current and future breast cancer screening programs. Specifically, M-BIG will provide clinical data to:1.investigate the effect of breast cancer screening on breast cancer prognosis and mortality;2.develop and validate the use of artificial intelligence and machine learning in breast image interpretation; and3.develop and validate image-based radiological breast cancer risk profiles.

Approach

The M-BIG database is intended to include a wide range of digital mammography (DM) and digital breast tomosynthesis (DBT) examinations performed on women at the Mammography Clinic in Malmö, Sweden, from the introduction of DM in 2004 through 2020. Subjects may be included multiple times and for diverse reasons. The image data are linked to extensive clinical, diagnostic, and demographic data from several registries.

Results

To date, the database contains a total of 451,054 examinations from 104,791 women. During the inclusion period, 95,258 unique women were screened. A total of 19,968 examinations were performed using DBT, whereas the rest used DM.

Conclusions

We describe the design and implementation of the M-BIG database as a representative and accessible medical image database linked to various types of medical data. Work is ongoing to add features and curate the existing data.

Perturbation and stability of PAM50 subtyping in population-based primary invasive breast cancer

PAM50 gene expression subtypes represent a cornerstone in the molecular classification of breast cancer and are included in risk prediction models to guide therapy. We aimed to illustrate the impact of included genes and biological processes on subtyping while considering a tumor's underlying clinical subgroup defined by ER, PR, and HER2 status. To do this we used a population-representative and clinically annotated early-stage breast tumor cohort of 6233 samples profiled by RNA sequencing and applied a perturbation strategy of excluding co-expressed genes (gene sets). We demonstrate how PAM50 nearest-centroid classification depends on biological processes present across, but also within, ER/PR/HER2 subgroups and PAM50 subtypes themselves. Our analysis highlights several key aspects of PAM50 classification. Firstly, we demonstrate the tight connection between a tumor's nearest and second-nearest PAM50 centroid. Additionally, we show that the second-best subtype is associated with overall survival in ER-positive, HER2-negative, and node-negative disease. We also note that ERBB2 expression has little impact on PAM50 classification in HER2-positive disease regardless of ER status and that the Basal subtype is highly stable in contrast to the Normal subtype. Improved consciousness of the commonly used PAM50 subtyping scheme will aid in our understanding and interpretation of breast tumors that have seemingly conflicting PAM50 classification when compared to clinical biomarkers. Finally, our study adds further support in challenging the common misconception that PAM50 subtypes are distinct classes by illustrating that PAM50 subtypes in tumors represent a continuum with prognostic implications.

Comparison of SP142 and 22C3 PD-L1 assays in a population-based cohort of triple-negative breast cancer patients in the context of their clinically established scoring algorithms

BACKGROUND

Immunohistochemical (IHC) PD-L1 expression is commonly employed as predictive biomarker for checkpoint inhibitors in triple-negative breast cancer (TNBC). However, IHC evaluation methods are non-uniform and further studies are needed to optimize clinical utility.

METHODS

We compared the concordance, prognostic value and gene expression between PD-L1 IHC expression by SP142 immune cell (IC) score and 22C3 combined positive score (CPS; companion IHC diagnostic assays for atezolizumab and pembrolizumab, respectively) in a population-based cohort of 232 early-stage TNBC patients.

RESULTS

The expression rates of PD-L1 for SP142 IC ≥ 1%, 22C3 CPS ≥ 10, 22C3 CPS ≥ 1 and 22C3 IC ≥ 1% were 50.9%, 27.2%, 53.9% and 41.8%, respectively. The analytical concordance (kappa values) between SP142 IC+ and these three different 22C3 scorings were 73.7% (0.48, weak agreement), 81.5% (0.63) and 86.6% (0.73), respectively. The SP142 assay was better at identifying 22C3 positive tumors than the 22C3 assay was at detecting SP142 positive tumors. PD-L1 (CD274) gene expression (mRNA) showed a strong positive association with all two-categorical IHC scorings of the PD-L1 expression, irrespective of antibody and cut-off (Spearman Rho ranged from 0.59 to 0.62; all p-values < 0.001). PD-L1 IHC positivity and abundance of tumor infiltrating lymphocytes were of positive prognostic value in univariable regression analyses in patients treated with (neo)adjuvant chemotherapy, where it was strongest for 22C3 CPS ≥ 10 and distant relapse-free interval (HR = 0.18, p = 0.019). However, PD-L1 status was not independently prognostic when adjusting for abundance of tumor infiltrating lymphocytes in multivariable analyses.

CONCLUSION

Our findings support that the SP142 and 22C3 IHC assays, with their respective clinically applied scoring algorithms, are not analytically equivalent where they identify partially non-overlapping subpopulations of TNBC patients and cannot be substituted with one another regarding PD-L1 detection. Trial registration The Swedish Cancerome Analysis Network - Breast (SCAN-B) study, retrospectively registered 2nd Dec 2014 at ClinicalTrials.gov; ID NCT02306096.

Matched analysis of circulating selenium with the breast cancer selenotranscriptome: a multicentre prospective study

INTRODUCTION

Low serum selenium and altered tumour RNA expression of certain selenoproteins are associated with a poor breast cancer prognosis. Selenoprotein expression stringently depends on selenium availability, hence circulating selenium may interact with tumour selenoprotein expression. However, there is no matched analysis to date.

METHODS

This study included 1453 patients with newly diagnosed breast cancer from the multicentric prospective Sweden Cancerome Analysis Network - Breast study. Total serum selenium, selenoprotein P and glutathione peroxidase 3 were analysed at time of diagnosis. Bulk RNA-sequencing was conducted in matched tumour tissues. Fully adjusted Cox regression models with an interaction term were employed to detect dose-dependent interactions of circulating selenium with the associations of tumour selenoprotein mRNA expression and mortality.

RESULTS

237 deaths were recorded within ~ 9 years follow-up. All three serum selenium biomarkers correlated positively (p < 0.001). All selenoproteins except for GPX6 were expressed in tumour tissues. Single cell RNA-sequencing revealed a heterogeneous expression pattern in the tumour microenvironment. Circulating selenium correlated positively with tumour SELENOW and SELENON expression (p < 0.001). In fully adjusted models, the associations of DIO1, DIO3 and SELENOM with mortality were dose-dependently modified by serum selenium (p < 0.001, p = 0.020, p = 0.038, respectively). With increasing selenium, DIO1 and SELENOM associated with lower, whereas DIO3 expression associated with higher mortality. Association of DIO1 with lower mortality was only apparent in patients with high selenium [above median (70.36 µg/L)], and the HR (95%CI) for one-unit increase in log(FPKM + 1) was 0.70 (0.50-0.98).

CONCLUSIONS

This first unbiased analysis of serum selenium with the breast cancer selenotranscriptome identified an effect-modification of selenium on the associations of DIO1, SELENOM, and DIO3 with prognosis. Selenium substitution in patients with DIO1-expressing tumours merits consideration to improve survival.

Alternative promoters and splicing create multiple functionally distinct isoforms of oestrogen receptor alpha in breast cancer and healthy tissues

BACKGROUND

Oestrogen receptor alpha (ER) is involved in cell growth and proliferation and functions as a transcription factor, a transcriptional coregulator, and in cytoplasmic signalling. It affects, for example, bone, endometrium, ovaries and mammary epithelium. It is a key biomarker in clinical management of breast cancer, where it is used as a prognostic and treatment-predictive factor, and a therapeutical target. Several ER isoforms have been described, but transcript annotation in public databases is incomplete and inconsistent, and functional differences are not well understood.

METHODS

We have analysed short- and long-read RNA sequencing data from breast tumours, breast cancer cell lines, and normal tissues to create a comprehensive annotation of ER transcripts and combined it with experimental studies of full-length protein and six alternative isoforms.

RESULTS

The isoforms have varying transcription factor activity, subcellular localisation, and response to the ER-targeting drugs tamoxifen and fulvestrant. Antibodies differ in ability to detect alternative isoforms, which raises concerns for the interpretation of ER-status in routine pathology.

CONCLUSIONS

Future work should investigate the effects of alternative isoforms on patient survival and therapy response. An accurate annotation of ER isoforms will aid in interpretation of clinical data and inform functional studies to improve our understanding of the ER in health and disease.

Functional In Vivo Screening Identifies microRNAs Regulating Metastatic Dissemination of Prostate Cancer Cells to Bone Marrow

Distant metastasis is the major cause of cancer-related deaths in men with prostate cancer (PCa). An in vivo functional screen was used to identify microRNAs (miRNAs) regulating metastatic dissemination of PCa cells. PC3 cells transduced with pooled miRZiP™ lentivirus library (anti-miRNAs) were injected intraprostatic to 13 NSG mice followed by targeted barcode/anti-miR sequencing. PCa cells in the primary tumours showed a homogenous pattern of anti-miRNAs, but different anti-miRNAs were enriched in liver, lung, and bone marrow, with anti-miR-379 highly enriched in the latter. The bone metastasis-promoting phenotype induced by decreased miR-379 levels was also confirmed in a less metastatic PCa cell line, 22Rv1, where all mice injected intracardially with anti-miR-379-22Rv1 cells developed bone metastases. The levels of miR-379 were found to be lower in bone metastases compared to primary tumours and non-cancerous prostatic tissue in a patient cohort. In vitro functional studies suggested that the mechanism of action was that reduced levels of miR-379 gave an increased colony formation capacity in conditions mimicking the bone microenvironment. In conclusion, our data suggest that specific miRNAs affect the establishment of primary tumours and metastatic dissemination, with a loss of miR-379 promoting metastases in bone.

FGF/FGFR1 system in paired breast tumor-adjacent and tumor tissues, associations with mammographic breast density and tumor characteristics

Introduction

Mammographic breast density (MBD) is an established breast cancer risk factor, yet the underlying molecular mechanisms remain to be deciphered. Fibroblast growth factor receptor 1 (FGFR1) amplification is associated with breast cancer development and aberrant FGF signaling found in the biological processes related to both high mammographic density and breast cancer microenvironment. The aim of this study was to investigate the FGF/FGFR1 expression in-between paired tumor-adjacent and tumor tissues from the same patient, and its associations with MBD and tumor characteristics.

Methods

FGFR1 expression in paired tissues from 426 breast cancer patients participating in the Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) cohort study was analyzed by immunohistochemistry. FGF ligand expression was obtained from RNA-sequencing data for 327 of the included patients.

Results

FGFR1 levels were differently expressed in tumor-adjacent and tumor tissues, with increased FGFR1 levels detected in 58% of the tumors. High FGFR1 expression in tumor tissues was associated with less favorable tumor characteristics; high histological grade (OR=1.86, 95% CI 1.00-3.44), high Ki67 proliferative index (OR=2.18, 95% CI 1.18-4.02) as well as tumors of Luminal B-like subtype (OR=2.56, 95%CI 1.29-5.06). While no clear association between FGFR1 expression and MBD was found, FGF ligand (FGF1, FGF11, FGF18) expression was positively correlated with MBD.

Discussion

Taken together, these findings support a role of the FGF/FGFR1 system in early breast cancer which warrants further investigation in the MBD-breast cancer context.

Serum copper, zinc and copper/zinc ratio in relation to survival after breast cancer diagnosis: A prospective multicenter cohort study

BACKGROUND

The essential trace elements copper and zinc, and their ratio (copper/zinc), are important for maintaining redox homeostasis. Previous studies suggest that these elements may impact breast cancer survival. However, no epidemiological study has so far been conducted on the potential association between copper and copper/zinc levels and survival after breast cancer diagnosis. In this study, we aimed to examine the relationship between serum copper, zinc and copper/zinc levels and survival following breast cancer diagnosis.

PATIENTS AND METHODS

The Sweden Cancerome Analysis Network - Breast Initiative (SCAN-B) is a population-based cohort study including multiple participating hospitals in Sweden. A total of 1998 patients diagnosed with primary invasive breast cancer were followed for approximately nine years. Serum levels of copper and zinc and their ratio at the time of diagnosis was analyzed in relation to breast cancer survival using multivariate Cox regression, yielding hazard ratios (HR) with 95% confidence intervals.

RESULTS

A higher copper/zinc ratio was associated with lower overall survival after breast cancer diagnosis. Comparing patients with a copper/zinc ratio in quartile 4 vs 1, the crude HR was 2.29 (1.65-3.19) (P_trend <0.01) and the fully adjusted HR was 1.58 (1.11-2.25) (P_trend = 0.01). No overall associations were seen between serum copper or zinc levels on their own and survival after breast cancer diagnosis, although a tendency toward lower breast cancer survival was seen for higher copper levels and lower zinc levels.

CONCLUSION

There is evidence that the serum copper/zinc ratio provides an independent predictive value for overall survival following breast cancer diagnosis.

Dependency of NELF-E-SLUG-KAT2B epigenetic axis in breast cancer carcinogenesis

Cancer cells undergo transcriptional reprogramming to drive tumor progression and metastasis. Using cancer cell lines and patient-derived tumor organoids, we demonstrate that loss of the negative elongation factor (NELF) complex inhibits breast cancer development through downregulating epithelial-mesenchymal transition (EMT) and stemness-associated genes. Quantitative multiplexed Rapid Immunoprecipitation Mass spectrometry of Endogenous proteins (qPLEX-RIME) further reveals a significant rewiring of NELF-E-associated chromatin partners as a function of EMT and a co-option of NELF-E with the key EMT transcription factor SLUG. Accordingly, loss of NELF-E leads to impaired SLUG binding on chromatin. Through integrative transcriptomic and genomic analyses, we identify the histone acetyltransferase, KAT2B, as a key functional target of NELF-E-SLUG. Genetic and pharmacological inactivation of KAT2B ameliorate the expression of EMT markers, phenocopying NELF ablation. Elevated expression of NELF-E and KAT2B is associated with poorer prognosis in breast cancer patients, highlighting the clinical relevance of our findings. Taken together, we uncover a crucial role of the NELF-E-SLUG-KAT2B epigenetic axis in breast cancer carcinogenesis.

Tamoxifen Response at Single Cell Resolution in Estrogen Receptor-Positive Primary Human Breast Tumors

In ER+/HER2- breast cancer, multiple measures of intra-tumor heterogeneity are associated with worse response to endocrine therapy. To investigate heterogeneity in response to treatment, we developed an operating room-to-laboratory pipeline for the collection of live human tumors and normal breast specimens immediately after surgical resection for processing into single-cell workflows for experimentation and genomic analyses. We demonstrate differences in tamoxifen response by cell type and identify distinctly responsive and resistant subpopulations within the malignant cell compartment of human tumors. Tamoxifen resistance signatures from 3 distinct resistant subpopulations are prognostic in large cohorts of ER+ breast cancer patients and enriched in endocrine therapy resistant tumors. This novel ex vivo model system now provides a foundation to define responsive and resistant sub-populations within heterogeneous tumors, to develop precise single cell-based predictors of response to therapy, and to identify genes and pathways driving resistance to therapy.

Molecular characteristics of breast tumors in patients screened for germline predisposition from a population-based observational study

BACKGROUND

Pathogenic germline variants (PGVs) in certain genes are linked to higher lifetime risk of developing breast cancer and can influence preventive surgery decisions and therapy choices. Public health programs offer genetic screening based on criteria designed to assess personal risk and identify individuals more likely to carry PGVs, dividing patients into screened and non-screened groups. How tumor biology and clinicopathological characteristics differ between these groups is understudied and could guide refinement of screening criteria.

METHODS

Six thousand six hundred sixty breast cancer patients diagnosed in South Sweden during 2010-2018 were included with available clinicopathological and RNA sequencing data, 900 (13.5%) of which had genes screened for PGVs through routine clinical screening programs. We compared characteristics of screened patients and tumors to non-screened patients, as well as between screened patients with (n = 124) and without (n = 776) PGVs.

RESULTS

Broadly, breast tumors in screened patients showed features of a more aggressive disease. However, few differences related to tumor biology or patient outcome remained significant after stratification by clinical subgroups or PAM50 subtypes. Triple-negative breast cancer (TNBC), the subgroup most enriched for PGVs, showed the most differences between screening subpopulations (e.g., higher tumor proliferation in screened cases). Significant differences in PGV prevalence were found between clinical subgroups/molecular subtypes, e.g., TNBC cases were enriched for BRCA1 PGVs. In general, clinicopathological differences between screened and non-screened patients mimicked those between patients with and without PGVs, e.g., younger age at diagnosis for positive cases. However, differences in tumor biology/microenvironment such as immune cell composition were additionally seen within PGV carriers/non-carriers in ER + /HER2 - cases, but not between screening subpopulations in this subgroup.

CONCLUSIONS

Characterization of molecular tumor features in patients clinically screened and not screened for PGVs represents a relevant read-out of guideline criteria. The general lack of molecular differences between screened/non-screened patients after stratification by relevant breast cancer subsets questions the ability to improve the identification of screening candidates based on currently used patient and tumor characteristics, pointing us towards universal screening. Nevertheless, while that is not attained, molecular differences identified between PGV carriers/non-carriers suggest the possibility of further refining patient selection within certain patient subsets using RNA-seq through, e.g., gene signatures.

TRIAL REGISTRATION

The Sweden Cancerome Analysis Network - Breast (SCAN-B) was prospectively registered at ClinicalTrials.gov under the identifier NCT02306096.

Convolutional neural network for biomarker discovery for triple negative breast cancer with RNA sequencing data

Triple negative breast cancers (TNBCs) are tumors with a poor treatment response and prognosis. In this study, we propose a new approach, candidate extraction from convolutional neural network (CNN) elements (CECE), for discovery of biomarkers for TNBCs. We used the GSE96058 and GSE81538 datasets to build a CNN model to classify TNBCs and non-TNBCs and used the model to make TNBC predictions for two additional datasets, the cancer genome atlas (TCGA) breast cancer RNA sequencing data and the data from Fudan University Shanghai Cancer Center (FUSCC). Using correctly predicted TNBCs from the GSE96058 and TCGA datasets, we calculated saliency maps for these subjects and extracted the genes that the CNN model used to separate TNBCs from non-TNBCs. Among the TNBC signature patterns that the CNN models learned from the training data, we found a set of 21 genes that can classify TNBCs into two major classes, or CECE subtypes, with distinct overall survival rates (P = 0.0074). We replicated this subtype classification in the FUSCC dataset using the same 21 genes, and the two subtypes had similar differential overall survival rates (P = 0.0490). When all TNBCs were combined from the 3 datasets, the CECE II subtype had a hazard ratio of 1.94 (95% CI, 1.25-3.01; P = 0.0032). The results demonstrate that the spatial patterns learned by the CNN models can be utilized to discover interacting biomarkers otherwise unlikely to be identified by traditional approaches.

Multi-omics and experimental analysis unveil theragnostic value and immunological roles of inner membrane mitochondrial protein (IMMT) in breast cancer

BACKGROUND

The inner membrane mitochondrial protein (IMMT) is a central unit of the mitochondrial contact site and cristae organizing system (MICOS). While researchers continue to demonstrate the physiological function of IMMT in regulating mitochondrial dynamics and preserving mitochondrial structural integrity, the roles of IMMT in clinicopathology, the tumor immune microenvironment (TIME), and precision oncology in breast cancer (BC) remain unclear.

METHODS

Multi-omics analysis was used here to evaluate the diagnostic and prognostic value of IMMT. Web applications aimed at analyzing the whole tumor tissue, single cells, and spatial transcriptomics were used to examine the relationship of IMMT with TIME. Gene set enrichment analysis (GSEA) was employed to determine the primary biological impact of IMMT. Experimental verification using siRNA knockdown and clinical specimens of BC patients confirmed the mechanisms behind IMMT on BC cells and the clinical significance, respectively. Potent drugs were identified by accessing the data repositories of CRISPR-based drug screenings.

RESULTS

High IMMT expression served as an independent diagnostic biomarker, correlated with advanced clinical status, and indicated a poor relapse-free survival (RFS) rate for patients with BC. Although, the contents of Th1, Th2, MSC, macrophages, basophil, CD4 + T cell and B cell, and TMB levels counteracted the prognostic significance. Single-cell level and whole-tissue level analyses revealed that high IMMT was associated with an immunosuppressive TIME. GSEA identified IMMT perturbation as involved in cell cycle progression and mitochondrial antioxidant defenses. Experimental knockdown of IMMT impeded the migration and viability of BC cells, arrested the cell cycle, disturbed mitochondrial function, and increased the ROS level and lipid peroxidation. The clinical values of IMMT were amenable to ethnic Chinese BC patients, and can be extrapolated to some other cancer types. Furthermore, we discovered that pyridostatin acted as a potent drug candidate in BC cells harboring an elevated IMMT expression.

CONCLUSION

This study combined a multi-omics survey with experimental verification to reveal the novel clinical significance of IMMT in BC, demonstrating its role in TIME, cancer cell growth and mitochondrial fitness, and identified pyridostatin as a promising drug candidate for the development of precision medicine.

Krüppel-like factor 9 (KLF9) links hormone dysregulation and circadian disruption to breast cancer pathogenesis

BACKGROUND

Circadian disruption is an emerging driver of breast cancer (BCa), with epidemiological studies linking shift work and chronic jet lag to increased BCa risk. Indeed, several clock genes participate in the gating of mitotic entry, regulation of DNA damage response, and epithelial-to-mesenchymal transition, thus impacting BCa etiology. Dysregulated estrogen (17β-estradiol, E2) and glucocorticoid (GC) signaling prevalent in BCa may further contribute to clock desynchrony by directly regulating the expression and cycling dynamics of genes comprising the local breast oscillator. In this study, we investigated the tumor suppressor gene, Krüppel-like factor 9 (KLF9), as an important point of crosstalk between hormone signaling and the circadian molecular network, and further examine its functional role in BCa.

METHODS

Through meta-analysis of publicly available RNA- and ChIP-sequencing datasets from BCa tumor samples and cell lines, and gene expression analysis by RT-qPCR and enhancer- reporter assays, we elucidated the molecular mechanism behind the clock and hormone regulation of KLF9. Lentiviral knockdown and overexpression of KLF9 in three distinct breast epithelial cell lines (MCF10A, MCF7 and MDA-MB-231) was generated to demonstrate the role of KLF9 in orthogonal assays on breast epithelial survival, proliferation, apoptosis, and migration.

RESULTS

We determined that KLF9 is a direct GC receptor target in mammary epithelial cells, and that induction is likely mediated through coordinate transcriptional activation from multiple GC-responsive enhancers in the KLF9 locus. More interestingly, rhythmic expression of KLF9 in MCF10A cells was abolished in the highly aggressive MDA-MB-231 line. In turn, forced expression of KLF9 altered the baseline and GC/E2-responsive expression of several clock genes, indicating that KLF9 may function as a regulator of the core clock machinery. Characterization of the role of KLF9 using complementary cancer hallmark assays in the context of the hormone-circadian axis revealed that KLF9 plays a tumor-suppressive role in BCa regardless of molecular subtype. KLF9 potentiated the anti-tumorigenic effects of GC in E2 receptor + luminal MCF7 cells, while it restrained GC-enhanced oncogenicity in triple-negative MCF10A and MDA-MB-231 cells.

CONCLUSIONS

Taken together, our findings support that dysregulation of KLF9 expression and oscillation in BCa impinges on circadian network dynamics, thus ultimately affecting the BCa oncogenic landscape.

CD169+ Macrophages in Primary Breast Tumors Associate with Tertiary Lymphoid Structures, Tregs and a Worse Prognosis for Patients with Advanced Breast Cancer

The presence of CD169⁺ macrophages in the draining lymph nodes of cancer patients is, for unknown reasons, associated with a beneficial prognosis. We here investigated the prognostic impact of tumor-infiltrating CD169⁺ macrophages in primary tumors (PTs) and their spatial relation to tumor-infiltrating B and T cells. Using two breast cancer patient cohorts, we show that CD169⁺ macrophages were spatially associated with the presence of B and T cell tertiary lymphoid-like structures (TLLSs) in both PTs and lymph node metastases (LNMs). While co-infiltration of CD169⁺/TLLS in PTs correlated with a worse prognosis, the opposite was found when present in LNMs. RNA sequencing of breast tumors further confirmed that SIGLEC1 (CD169) expression was associated with mature tertiary lymphoid structure (TLS), and T_reg and B_reg signatures. We propose that the negative prognostic value related to CD169⁺ macrophages in PTs is a consequence of an immunosuppressive tumor environment rich in TLSs, T_regs and B_regs.

Expression of hormone receptors is associated with specific immunological profiles of the breast cancer microenvironment

BACKGROUND

Elucidating the unique immunoregulatory mechanisms in breast cancer microenvironment may help develop new therapeutic strategies. Some studies have suggested that hormone receptors also have immune regulatory functions, but their mechanisms are not fully understood. In this study, we have comprehensively analyzed the relationship between the expressions of estrogen (ER), progesterone (PgR), and androgen receptors (AR), and the immunological profile in breast cancer.

METHODS

Using publicly available gene expression profile datasets, METABRIC and SCAN-B, the associations between the expressions of hormone receptors and the immune cell compositions in breast cancer tissue, estimated by CIBERSORTx algorithm, were analyzed. We histologically evaluated tumor-infiltrating lymphocytes (hTIL), PD-L1 (hPD-L1) expression, and the infiltration of 11 types of immune cells by flow cytometry (FCM) for 45 breast cancer tissue samples. The relationships between them and the expressions of ER, PgR, and AR of tumor tissues, evaluated immunohistochemically, were analyzed.

RESULTS

Expressions of ESR1, PGR, and AR were negatively correlated with overall immune composition. Expressions of ER and AR, but not that of PgR, were inversely associated with hTIL and hPD-L1 expression. FCM analysis showed that the expressions of ER and AR, but not that of PgR, were associated with decreased total leukocyte infiltration. Both CIBERSORTx and FCM analysis showed that ER expression was associated with reduced infiltration of macrophages and CD4+ T cells and that of AR with reduced macrophage infiltration.

CONCLUSION

Hormone receptor expression correlates with specific immunological profiles in the breast cancer microenvironment both at the gene and protein expression levels.

RNA-Based Classification of Homologous Recombination Deficiency in Racially Diverse Patients with Breast Cancer

BACKGROUND

Aberrant expression of DNA repair pathways such as homologous recombination (HR) can lead to DNA repair imbalance, genomic instability, and altered chemotherapy response. DNA repair imbalance may predict prognosis, but variation in DNA repair in diverse cohorts of breast cancer patients is understudied.

METHODS

To identify RNA-based patterns of DNA repair expression, we performed unsupervised clustering on 51 DNA repair-related genes in the Cancer Genome Atlas Breast Cancer [TCGA BRCA (n = 1,094)] and Carolina Breast Cancer Study [CBCS (n = 1,461)]. Using published DNA-based HR deficiency (HRD) scores (high-HRD ≥ 42) from TCGA, we trained an RNA-based supervised classifier. Unsupervised and supervised HRD classifiers were evaluated in association with demographics, tumor characteristics, and clinical outcomes.

RESULTS

: Unsupervised clustering on DNA repair genes identified four clusters of breast tumors, with one group having high expression of HR genes. Approximately 39.7% of CBCS and 29.3% of TCGA breast tumors had this unsupervised high-HRD (U-HRD) profile. A supervised HRD classifier (S-HRD) trained on TCGA had 84% sensitivity and 73% specificity to detect HRD-high samples. Both U-HRD and S-HRD tumors in CBCS had higher frequency of TP53 mutant-like status (45% and 41% enrichment) and basal-like subtype (63% and 58% enrichment). S-HRD high was more common among black patients. Among chemotherapy-treated participants, recurrence was associated with S-HRD high (HR: 2.38, 95% confidence interval = 1.50-3.78).

CONCLUSIONS

HRD is associated with poor prognosis and enriched in the tumors of black women.

IMPACT

RNA-level indicators of HRD are predictive of breast cancer outcomes in diverse populations.

Choice of High-Throughput Proteomics Method Affects Data Integration with Transcriptomics and the Potential Use in Biomarker Discovery

In recent years, several advances have been achieved in breast cancer (BC) classification and treatment. However, overdiagnosis, overtreatment, and recurrent disease are still significant causes of complication and death. Here, we present the development of a protocol aimed at parallel transcriptome and proteome analysis of BC tissue samples using mass spectrometry, via Data Dependent and Independent Acquisitions (DDA and DIA). Protein digestion was semi-automated and performed on flowthroughs after RNA extraction. Data for 116 samples were acquired in DDA and DIA modes and processed using MaxQuant, EncyclopeDIA, or DIA-NN. DIA-NN showed an increased number of identified proteins, reproducibility, and correlation with matching RNA-seq data, therefore representing the best alternative for this setup. Gene Set Enrichment Analysis pointed towards complementary information being found between transcriptomic and proteomic data. A decision tree model, designed to predict the intrinsic subtypes based on differentially abundant proteins across different conditions, selected protein groups that recapitulate important clinical features, such as estrogen receptor status, HER2 status, proliferation, and aggressiveness. Taken together, our results indicate that the proposed protocol performed well for the application. Additionally, the relevance of the selected proteins points to the possibility of using such data as a biomarker discovery tool for personalized medicine.

Clinicopathological Features and Outcomes Comparing Patients With Invasive Ductal and Lobular Breast Cancer

BACKGROUND

There is increasing interest in better understanding the biology and clinical presentation of invasive lobular cancer (ILC), which is the most common special histological subtype of breast cancer. Limited large contemporary data sets are available allowing comparison of clinicopathologic features between ILC and invasive ductal cancer (IDC).

METHODS

The Great Lakes Breast Cancer Consortium was formed to compare clinical behavior of ILC (n = 3617) and IDC (n = 30 045) from 33 662 patients treated between 1990 and 2017 at 3 large clinical centers. We used Kaplan-Meier analysis, Cox proportional hazards modeling, and propensity score matching to evaluate treatment differences and outcomes. All statistical testing used 2-sided P values.

RESULTS

Compared with IDC, patients with ILC were more frequently diagnosed at later stages and with more lymph node involvement (corrected P < .001). Estrogen receptor-positive ILCs were of lower grade (grade 1 and 2: 90% in ILC vs 72% in IDC) but larger in size (T3 and 4: 14.3% in ILC vs 3.4% in IDC) (corrected P < .001), and since 1990, the mean ILC size detected at diagnosis increased yearly. Patients with estrogen receptor (ER)-positive ILC underwent statistically significantly more mastectomies compared with ER-positive IDC (57% vs 46%). Using Kaplan-Meier analysis, patients with ER-positive ILC had statistically significantly worse disease-free survival and overall survival than ER-positive IDC although 6 times more IDCs were classified as high risk by OncotypeDx Breast Recurrence Score assay.

CONCLUSIONS

This large, retrospective, collaborative analysis with 3 clinical centers identified meaningful differences in clinicopathological features between ILC and IDC, providing further evidence that these are 2 different entities requiring different clinical management.

How Reliable Are Gene Expression-Based and Immunohistochemical Biomarkers Assessed on a Core-Needle Biopsy? A Study of Paired Core-Needle Biopsies and Surgical Specimens in Early Breast Cancer

In early breast cancer, a preoperative core-needle biopsy (CNB) is vital to confirm the malignancy of suspected lesions and for assessing the expression of treatment predictive and prognostic biomarkers in the tumor to choose the optimal treatments, emphasizing the importance of obtaining reliable results when biomarker status is assessed on a CNB specimen. This study aims to determine the concordance between biomarker status assessed as part of clinical workup on a CNB compared to a medically untreated surgical specimen. Paired CNB and surgical specimens from 259 patients that were part of the SCAN-B cohort were studied. The concordance between immunohistochemical (IHC) and gene expression (GEX) based biomarker status was investigated. Biomarkers of interest included estrogen receptor (ER; specifically, the alpha variant), progesterone receptor (PgR), Ki67, HER2, and tumor molecular subtype. In general, moderate to very good correlation in biomarker status between the paired CNB and surgical specimens was observed for both IHC assessment (83–99% agreement, kappa range 0.474–0.917) and GEX assessment (70–97% agreement, kappa range 0.552–0.800), respectively. However, using IHC, 52% of cases with low Ki67 status in the CNB shifted to high Ki67 status in the surgical specimen (McNemar’s p = 0.011). Similarly, when using GEX, a significant shift from negative to positive ER (47%) and from low to high Ki67 (16%) was observed between the CNB and surgical specimen (McNemar’s p = 0.027 and p = 0.002 respectively). When comparing biomarker status between different techniques (IHC vs. GEX) performed on either CNBs or surgical specimens, the agreement in ER, PgR, and HER2 status was generally over 80% in both CNBs and surgical specimens (kappa range 0.395–0.708), but Ki67 and tumor molecular subtype showed lower concordance levels between IHC and GEX (48–62% agreement, kappa range 0.152–0.398). These results suggest that both the techniques used for collecting tissue samples and analyzing biomarker status have the potential to affect the results of biomarker assessment, potentially also impacting treatment decisions and patient survival outcomes.

Subtype and cell type specific expression of lncRNAs provide insight into breast cancer

Long non-coding RNAs (lncRNAs) are involved in breast cancer pathogenesis through chromatin remodeling, transcriptional and post-transcriptional gene regulation. We report robust associations between lncRNA expression and breast cancer clinicopathological features in two population-based cohorts: SCAN-B and TCGA. Using co-expression analysis of lncRNAs with protein coding genes, we discovered three distinct clusters of lncRNAs. In silico cell type deconvolution coupled with single-cell RNA-seq analyses revealed that these three clusters were driven by cell type specific expression of lncRNAs. In one cluster lncRNAs were expressed by cancer cells and were mostly associated with the estrogen signaling pathways. In the two other clusters, lncRNAs were expressed either by immune cells or fibroblasts of the tumor microenvironment. To further investigate the cis-regulatory regions driving lncRNA expression in breast cancer, we identified subtype-specific transcription factor (TF) occupancy at lncRNA promoters. We also integrated lncRNA expression with DNA methylation data to identify long-range regulatory regions for lncRNA which were validated using ChiA-Pet-Pol2 loops. lncRNAs play an important role in shaping the gene regulatory landscape in breast cancer. We provide a detailed subtype and cell type-specific expression of lncRNA, which improves the understanding of underlying transcriptional regulation in breast cancer.

RNA sequencing-based single sample predictors of molecular subtype and risk of recurrence for clinical assessment of early-stage breast cancer

Multigene assays for molecular subtypes and biomarkers can aid management of early invasive breast cancer. Using RNA-sequencing we aimed to develop single-sample predictor (SSP) models for clinical markers, subtypes, and risk of recurrence (ROR). A cohort of 7743 patients was divided into training and test set. We trained SSPs for subtypes and ROR assigned by nearest-centroid (NC) methods and SSPs for biomarkers from histopathology. Classifications were compared with Prosigna in two external cohorts (ABiM, n = 100 and OSLO2-EMIT0, n = 103). Prognostic value was assessed using distant recurrence-free interval. Agreement between SSP and NC for PAM50 (five subtypes) was high (85%, Kappa = 0.78) for Subtype (four subtypes) very high (90%, Kappa = 0.84) and for ROR risk category high (84%, Kappa = 0.75, weighted Kappa = 0.90). Prognostic value was assessed as equivalent and clinically relevant. Agreement with histopathology was very high or high for receptor status, while moderate for Ki67 status and poor for Nottingham histological grade. SSP and Prosigna concordance was high for subtype (OSLO-EMIT0 83%, Kappa = 0.73 and ABiM 80%, Kappa = 0.72) and moderate and high for ROR risk category (68 and 84%, Kappa = 0.50 and 0.70, weighted Kappa = 0.70 and 0.78). Pooled concordance for emulated treatment recommendation dichotomized for chemotherapy was high (85%, Kappa = 0.66). Retrospective evaluation suggested that SSP application could change chemotherapy recommendations for up to 17% of postmenopausal ER+/HER2-/N0 patients with balanced escalation and de-escalation. Results suggest that NC and SSP models are interchangeable on a group-level and nearly so on a patient level and that SSP models can be derived to closely match clinical tests.

One-year recovery from breast cancer: Importance of tumor and treatment-related factors, resilience, and sociodemographic factors for health-related quality of life

Aim

This study investigated the changes in health-related quality of life from diagnosis to 1 year after diagnosis in breast cancer (BC) patients and the influence of clinical, psychological, and sociodemographic variables. An additional aim was to explore the mediating and moderating effects of resilience on changes in health-related quality of life.

Methods

A longitudinal population-based study was conducted in southern Sweden. Newly diagnosed BC patients filled in measures of health-related quality of life, resilience, and sociodemographic variables at diagnosis (N = 980) and 1 year post-diagnosis (N = 780). Clinical variables were extracted from the Swedish national breast cancer quality registry. Mixed-model analyses were performed.

Results

Most health-related quality of life outcomes declined from diagnosis to 1 year post-diagnosis. Role limitations due to emotional problems remained the same, whereas mental health improved. Lower health-related quality of life outcomes were associated with symptomatic detection and axillary dissection. Patients with a higher TNM stage and histologic grade and estrogen receptor (ER)-negative and human epidermal growth factor 2 (HER2)-positive status, who received chemotherapy, antibody therapy, or bisphosphonate therapy, had a steeper decline in outcomes. Changes in resilience were positively associated with all outcomes but did not mediate or moderate changes in any. Resilience at baseline moderated changes in bodily pain, vitality, and mental health, with higher baseline resilience being associated with a steeper decline, possibly due to floor or ceiling effects. Patients with lower socioeconomic status, educational level, and older age had a lower health-related quality of life.

Conclusion

Physical health-related quality of life among breast cancer patients declined 1 year post-diagnosis, whereas mental health-related quality of life improved. Low resilient patients may be especially vulnerable at diagnosis. Biopsychosocial assessment at diagnosis can help identify patients who may require additional support. A multidimensional treatment plan should be started early to help overcome the problems in everyday activities.

Discovery and validation of a transcriptional signature identifying homologous recombination-deficient breast, endometrial and ovarian cancers

BACKGROUND

Molecular alterations leading to homologous recombination deficiency (HRD) are heterogeneous. We aimed to identify a transcriptional profile shared by endometrial (UCEC), breast (BRCA) and ovarian (OV) cancers with HRD.

METHODS

Genes differentially expressed with HRD genomic score (continuous gHRD score) in UCEC/BRCA/OV were identified using edgeR, and used to train a RNAseq score (ridge-regression model) predictive of the gHRD score (PanCanAtlas, N = 1684 samples). The RNAseq score was applied in independent gynaecological datasets (CARPEM/CPTAC/SCAN/TCGA, N = 4038 samples). Validations used ROC curves, linear regressions and Pearson correlations. Overall survival (OS) analyses used Kaplan-Meier curves and Cox models.

RESULTS

In total, 656 genes were commonly up/downregulated with gHRD score in UCEC/BRCA/OV. Upregulated genes were enriched for nuclear/chromatin/DNA-repair processes, while downregulated genes for cytoskeleton (gene ontologies). The RNAseq score correlated with gHRD score in independent gynaecological cancers (R² = 0.4-0.7, Pearson correlation = 0.64-0.86, all P < 10^-11), and was predictive of gHRD score >42 (RNAseq HRD profile; AUC = 0.95/0.92/0.78 in UCEC/BRCA/OV). RNAseq HRD profile was associated (i) with better OS in platinum-treated advanced TP53-mutated-UCEC (P < 0.001) and OV (P = 0.013), and (ii) with poorer OS (P < 0.001) and higher benefit of adjuvant chemotherapy in Stage I-III BRCA (interaction test, P < 0.001).

CONCLUSIONS

UCEC/BRCA/OV with HRD-associated genomic scars share a common transcriptional profile. RNAseq signatures might be relevant for identifying HRD-gynaecological cancers, for prognostication and for therapeutic decision.

MicroRNA-449a Inhibits Triple Negative Breast Cancer by Disturbing DNA Repair and Chromatid Separation

Chromosomal instability (CIN) can be a driver of tumorigenesis but is also a promising therapeutic target for cancer associated with poor prognosis such as triple negative breast cancer (TNBC). The treatment of TNBC cells with defects in DNA repair genes with poly(ADP-ribose) polymerase inhibitor (PARPi) massively increases CIN, resulting in apoptosis. Here, we identified a previously unknown role of microRNA-449a in CIN. The transfection of TNBC cell lines HCC38, HCC1937 and HCC1395 with microRNA-449a mimics led to induced apoptosis, reduced cell proliferation, and reduced expression of genes in homology directed repair (HDR) in microarray analyses. EME1 was identified as a new target gene by immunoprecipitation and luciferase assays. The reduced expression of EME1 led to an increased frequency of ultrafine bridges, 53BP1 foci, and micronuclei. The induced expression of microRNA-449a elevated CIN beyond tolerable levels and induced apoptosis in TNBC cell lines by two different mechanisms: (I) promoting chromatid mis-segregation by targeting endonuclease EME1 and (II) inhibiting HDR by downregulating key players of the HDR network such as E2F3, BIRC5, BRCA2 and RAD51. The ectopic expression of microRNA-449a enhanced the toxic effect of PARPi in cells with pathogenic germline BRCA1 variants. The newly identified role makes microRNA-449a an interesting therapeutic target for TNBC.

Privacy preserving validation for multiomic prediction models

Reproducibility of results obtained using ribonucleic acid (RNA) data across labs remains a major hurdle in cancer research. Often, molecular predictors trained on one dataset cannot be applied to another due to differences in RNA library preparation and quantification, which inhibits the validation of predictors across labs. While current RNA correction algorithms reduce these differences, they require simultaneous access to patient-level data from all datasets, which necessitates the sharing of training data for predictors when sharing predictors. Here, we describe SpinAdapt, an unsupervised RNA correction algorithm that enables the transfer of molecular models without requiring access to patient-level data. It computes data corrections only via aggregate statistics of each dataset, thereby maintaining patient data privacy. Despite an inherent trade-off between privacy and performance, SpinAdapt outperforms current correction methods, like Seurat and ComBat, on publicly available cancer studies, including TCGA and ICGC. Furthermore, SpinAdapt can correct new samples, thereby enabling unbiased evaluation on validation cohorts. We expect this novel correction paradigm to enhance research reproducibility and to preserve patient privacy.

Clinical associations of ESR2 (estrogen receptor beta) expression across thousands of primary breast tumors

Estrogen receptor alpha (ERα, encoded by ESR1) is a well-characterized transcription factor expressed in more than 75% of breast tumors and is the key biomarker to direct endocrine therapies. On the other hand, much less is known about estrogen receptor beta (ERβ, encoded by ESR2) and its importance in cancer. Previous studies had some disagreement, however most reports suggested a more favorable prognosis for patients with high ESR2 expression. To add further clarity to ESR2 in breast cancer, we interrogated a large population-based cohort of primary breast tumors (n = 3207) from the SCAN-B study. RNA-seq shows ESR2 is expressed at low levels overall with a slight inverse correlation to ESR1 expression (Spearman R = −0.18, p = 2.2e−16), and highest ESR2 expression in the basal- and normal-like PAM50 subtypes. ESR2-high tumors had favorable overall survival (p = 0.006), particularly in subgroups receiving endocrine therapy (p = 0.03) and in triple-negative breast cancer (p = 0.01). These results were generally robust in multivariable analyses accounting for patient age, tumor size, node status, and grade. Gene modules consistent with immune response were associated to ESR2-high tumors. Taken together, our results indicate that ESR2 is generally expressed at low levels in breast cancer but associated with improved overall survival and may be related to immune response modulation.

High RAD51 gene expression is associated with aggressive biology and with poor survival in breast cancer

PURPOSE

Although the DNA repair mechanism is important in preventing carcinogenesis, its activation in established cancer cells may support their proliferation and aggravate cancer progression. RAD51 cooperates with BRCA2 and is essential in the homologous recombination of DNA repair. To this end, we hypothesized that RAD51 gene expression is associated with cancer cell proliferation and poor prognosis of breast cancer (BC) patients.

METHODS

A total of 8515 primary BC patients with transcriptome and clinical data from 17 independent cohorts were analyzed. The median value was used to divide each cohort into high and low RAD51 expression groups.

RESULTS

High RAD51 expression enriched the DNA repair gene set and was correlated with DNA repair-related genes. Nottingham histological grade, Ki67 expression and cell proliferation-related gene sets (E2F Targets, G2M Checkpoint and Myc Targets) were all significantly associated with the high RAD51 BC group. RAD51 expression was positively correlated with Homologous Recombination Deficiency, as well as both mutational burden and neoantigens that accompanied a higher infiltration of immune cells. Primary BC with lymph node metastases was associated with high expression of RAD51 in two cohorts. There was no strong correlation between RAD51 expression and drug sensitivity in cell lines, and RAD51 expression was lower after the neoadjuvant chemotherapy compared to before the treatment. High RAD51 BC was associated with poor prognosis consistently in three independent cohorts.

CONCLUSION

RAD51 gene expression is associated with aggressive cancer biology, cancer cell proliferation, and poor survival in breast cancer.

Differential Survival and Therapy Benefit of Patients with Breast Cancer Are Characterized by Distinct Epithelial and Immune Cell Microenvironments

PURPOSE

Extensive work in preclinical models has shown that microenvironmental cells influence many aspects of cancer cell behavior, including metastatic potential and their sensitivity to therapeutics. In the human setting, this behavior is mainly correlated with the presence of immune cells. Here, in addition to T cells, B cells, macrophages, and mast cells, we identified the relevance of nonimmune cell types for breast cancer survival and therapy benefit, including fibroblasts, myoepithelial cells, muscle cells, endothelial cells, and seven distinct epithelial cell types.

EXPERIMENTAL DESIGN

Using single-cell sequencing data, we generated reference profiles for all these cell types. We used these reference profiles in deconvolution algorithms to optimally detangle the cellular composition of more than 3,500 primary breast tumors of patients that were enrolled in the SCAN-B and MATADOR clinical trials, and for which bulk mRNA sequencing data were available.

RESULTS

This large data set enables us to identify and subsequently validate the cellular composition of microenvironments that distinguish differential survival and treatment benefit for different treatment regimens in patients with primary breast cancer. In addition to immune cells, we have identified that survival and therapy benefit are characterized by various contributions of distinct epithelial cell types.

CONCLUSIONS

From our study, we conclude that differential survival and therapy benefit of patients with breast cancer are characterized by distinct microenvironments that include specific populations of immune and epithelial cells.

Regulatory networks and 5' partner usage of miRNA host gene fusions in breast cancer

Genomic rearrangements in cancer cells can create gene fusions where the juxtaposition of two different genes leads to the production of chimeric proteins or altered gene expression through promoter‐swapping. We have previously shown that fusion transcripts involving microRNA (miRNA) host genes contribute to deregulation of miRNA expression regardless of the protein‐coding potential of these transcripts. Many different genes can also be used as 5′ partners by a miRNA host gene in what we named recurrent miRNA‐convergent fusions. Here, we have explored the properties of 5′ partners in fusion transcripts that involve miRNA hosts in breast tumours from The Cancer Genome Atlas (TCGA). We hypothesised that firstly, 5′ partner genes should belong to pathways and transcriptional programmes that reflect the tumour phenotype and secondly, there should be a selection for fusion events that shape miRNA expression to benefit the tumour cell through the known hallmarks of cancer. We found that the set of 5′ partners in miRNA host fusions is non‐random, with overrepresentation of highly expressed genes in pathways active in cancer including epithelial‐to‐mesenchymal transition, translational regulation and oestrogen signalling. Furthermore, many miRNAs were upregulated in samples with host gene fusions, including established oncogenic miRNAs such as mir‐21 and the mir‐106b~mir‐93~mir‐25 cluster. To the list of mechanisms for deregulation of miRNA expression, we have added fusion transcripts that change the promoter region. We propose that this adds material for genetic selection and tumour evolution in cancer cells and that miRNA host fusions can act as tumour ‘drivers’.

Intratumoral lymphatic endothelial cell infiltration reflecting lymphangiogenesis is counterbalanced by immune responses and better cancer biology in the breast cancer tumor microenvironment

Lymphangiogenesis, the generation of new lymphatic vessels from existing ones, results from the dynamic interactions of lymphatic endothelial cells and the tumor microenvironment (TME). It is well known that lymphangiogenesis occurs during the initial stage of metastasis in various types of malignant tumors. However, it is currently not used as a biomarker partially because gold standard method to quantify it is labor and cost intensive. We hypothesized that the quantity of intratumoral lymphatic endothelial cells (iLECs) in the TME is an indicator of lymphangiogenesis and a predictor of metastatic potential and overall survival in breast cancer. We analyzed a total of 4145 breast cancer patients from the Cancer Genome Atlas (TCGA) and GSE96058 by quantifying their iLECs using the xCell algorithm, and correlated these scores with patient survival, tumor grade, and cancer stage. We also assessed various pro- and anti-cancer gene sets for each tumor to characterize tumor behavior and aggressiveness. As we expected, high-iLEC breast cancer demonstrated enriched lymphoangiogenesis and angiogenesis gene sets and was associated with increased expressions of related genes. Also enriched were inflammatory response and immune response-related gene sets; IL2/STAT5 pathway, IL6/JAK/STAT3 pathway, TNFα pathway, allograft rejection, and complement as well as cancer stemness related gene sets like Notch signaling, Hedgehog signaling, epithelial mesenchymal transition, and Wnt beta-catenin signaling. Tumors with high-iLEC showed higher proportions of stromal cells and fewer anti-cancer immune cells. On the other hand, iLEC score did not correlate with patient survival or lymph node metastasis. Surprisingly, breast cancers with fewer iLECs demonstrated enriched E2F Targets, G2M Checkpoint, MYC Targets v1, and MTORC1 signaling which are cancer cell proliferation-related gene sets and exhibited an abundance of pro-cancer immune cells. The amount of iLEC correlated inversely with Ki67 expression and histological grade, which is in agreement that low-iLEC breast cancer was associated with enhanced cancer cell proliferation. In conclusion, while iLECs can be used as a surrogate for lymphangiogenesis in breast cancer, low-iLEC tumors also exhibit features which correspond to aggressive tumor biology, which may explain why the amount of iLECs was not associated with patient survival in our cohorts.

Sample Preparation Approach Influences PAM50 Risk of Recurrence Score in Early Breast Cancer

The PAM50 gene expression subtypes and the associated risk of recurrence (ROR) score are used to predict the risk of recurrence and the benefits of adjuvant therapy in early-stage breast cancer. The Prosigna assay includes the PAM50 subtypes along with their clinicopathological features, and is approved for treatment recommendations for adjuvant hormonal therapy and chemotherapy in hormone-receptor-positive early breast cancer. The Prosigna test utilizes RNA extracted from macrodissected tumor cells obtained from formalin-fixed, paraffin-embedded (FFPE) tissue sections. However, RNA extracted from fresh-frozen (FF) bulk tissue without macrodissection is widely used for research purposes, and yields high-quality RNA for downstream analyses. To investigate the impact of the sample preparation approach on ROR scores, we analyzed 94 breast carcinomas included in an observational study that had available gene expression data from macrodissected FFPE tissue and FF bulk tumor tissue, along with the clinically approved Prosigna scores for the node-negative, hormone-receptor-positive, HER2-negative cases (n = 54). ROR scores were calculated in R; the resulting two sets of scores from FFPE and FF samples were compared, and treatment recommendations were evaluated. Overall, ROR scores calculated based on the macrodissected FFPE tissue were consistent with the Prosigna scores. However, analyses from bulk tissue yielded a higher proportion of cases classified as normal-like; these were samples with relatively low tumor cellularity, leading to lower ROR scores. When comparing ROR scores (low, intermediate, and high), discordant cases between the two preparation approaches were revealed among the luminal tumors; the recommended treatment would have changed in a minority of cases.